Sequencing the functional antibody repertoire--diagnostic and therapeutic discovery

The multilevel extensive diversity across the cynomolgus macaque captured by ultra-deep adaptive immune receptor repertoire sequencing

The extent to which AIRRs differ among and within individuals remains elusive. Via ultra-deep repertoire sequencing of 22 and 25 tissues in three cynomolgus macaques, respectively, we identified 84 and 114 novel IGHV and TRBV alleles, confirming 72 (85.71%) and 100 (87.72%) of them. The heterogeneous V gene usage patterns were influenced, in turn, by genetics, isotype (for BCRs only), tissue group, and tissue. A higher proportion of intragroup shared clones in the intestinal tissues than those in other tissues suggests a close intra-intestinal adaptive immunity network. Significantly higher mutation burdens in the public clones and the inter-tissue shared IgM and IgD clones indicate that they might target the shared antigens. This study reveals the extensive heterogeneity of the AIRRs at various levels and has broad fundamental and clinical implications. The data generated here will serve as an invaluable resource for future studies on adaptive immunity in health and diseases.

The dengue-specific immune response and antibody identification with machine learning

Dengue virus poses a serious threat to global health and there is no specific therapeutic for it. Broadly neutralizing antibodies recognizing all serotypes may be an effective treatment. High-throughput adaptive immune receptor repertoire sequencing (AIRR-seq) and bioinformatic analysis enable in-depth understanding of the B-cell immune response. Here, we investigate the dengue antibody response with these technologies and apply machine learning to identify rare and underrepresented broadly neutralizing antibody sequences. Dengue immunization elicited the following signatures on the antibody repertoire: (i) an increase of CDR3 and germline gene diversity; (ii) a change in the antibody repertoire architecture by eliciting power-law network distributions and CDR3 enrichment in polar amino acids; (iii) an increase in the expression of JNK/Fos transcription factors and ribosomal proteins. Furthermore, we demonstrate the applicability of computational methods and machine learning to AIRR-seq datasets for neutralizing antibody candidate sequence identification. Antibody expression and functional assays have validated the obtained results.

Current advancements in B-cell receptor sequencing fast-track the development of synthetic antibodies

Synthetic antibodies (Abs) are a class of engineered proteins designed to mimic the functions of natural Abs. These are produced entirely in vitro, eliminating the need for an immune response. As such, synthetic Abs have transformed the traditional methods of raising Abs. Likewise, deep sequencing technologies have revolutionized genomics and molecular biology. These enable the rapid and cost-effective sequencing of DNA and RNA molecules. They have allowed for accurate and inexpensive analysis of entire genomes and transcriptomes. Notably, via deep sequencing it is now possible to sequence a person's entire B-cell receptor immune repertoire, termed BCR sequencing. This procedure allows for big data explorations of natural Abs associated with an immune response. Importantly, the identified sequences have the ability to improve the design and engineering of synthetic Abs by offering an initial sequence framework for downstream optimizations. Additionally, machine learning algorithms can be introduced to leverage the vast amount of BCR sequencing datasets to rapidly identify patterns hidden in big data to effectively make in silico predictions of antigen selective synthetic Abs. Thus, the convergence of BCR sequencing, machine learning, and synthetic Ab development has effectively promoted a new era in Ab therapeutics. The combination of these technologies is driving rapid advances in precision medicine, diagnostics, and personalized treatments.

The clinical applications of immunosequencing

Technological advances in high-throughput sequencing have opened the door for the interrogation of adaptive immune responses at unprecedented scale. It is now possible to determine the sequences of antibodies or T-cell receptors produced by individual B and T cells in a sample. This capability, termed immunosequencing, has transformed the study of both infectious and non-infectious diseases by allowing the tracking of dynamic changes in B and T cell clonal populations over time. This has improved our understanding of the pathology of cancers, autoimmune diseases, and infectious diseases. However, to date there has been only limited clinical adoption of the technology. Advances over the last decade and on the horizon that reduce costs and improve interpretability could enable widespread clinical use. Many clinical applications have been proposed and, while most are still undergoing research and development, some methods relying on immunosequencing data have been implemented, the most widespread of which is the detection of measurable residual disease. Here, we review the diagnostic, prognostic, and therapeutic applications of immunosequencing for both infectious and non-infectious diseases.

Redefining serological diagnostics with immunoaffinity proteomics

Serological diagnostics is generally defined as the detection of specific human immunoglobulins developed against viral, bacterial, or parasitic diseases. Serological tests facilitate the detection of past infections, evaluate immune status, and provide prognostic information. Serological assays were traditionally implemented as indirect immunoassays, and their design has not changed for decades. The advantages of straightforward setup and manufacturing, analytical sensitivity and specificity, affordability, and high-throughput measurements were accompanied by limitations such as semi-quantitative measurements, lack of universal reference standards, potential cross-reactivity, and challenges with multiplexing the complete panel of human immunoglobulin isotypes and subclasses. Redesign of conventional serological tests to include multiplex quantification of immunoglobulin isotypes and subclasses, utilize universal reference standards, and minimize cross-reactivity and non-specific binding will facilitate the development of assays with higher diagnostic specificity. Improved serological assays with higher diagnostic specificity will enable screenings of asymptomatic populations and may provide earlier detection of infectious diseases, autoimmune disorders, and cancer. In this review, we present the major clinical needs for serological diagnostics, overview conventional immunoassay detection techniques, present the emerging immunoassay detection technologies, and discuss in detail the advantages and limitations of mass spectrometry and immunoaffinity proteomics for serological diagnostics. Finally, we explore the design of novel immunoaffinity-proteomic assays to evaluate cell-mediated immunity and advance the sequencing of clinically relevant immunoglobulins.

Biomarkers to guide immunomodulatory treatment: where do we stand?

INTRODUCTION

This review summarizes current progress in the development of biomarkers to guide immunotherapy in oncology, rheumatology, and critical illness.

AREAS COVERED

An extensive literature search was performed about biomarkers classifying patients' immune responses to guide immunotherapy in oncology, rheumatology, and critical illness. Surface markers, such as programmed death-ligand 1 (PD-L1), genetic biomarkers, such as tumor mutation load, and circulating tumor DNA are biomarkers associated with the effectiveness of immunotherapy in oncology. Genomics, metabolomics, and proteomics play a crucial role in selecting the most suitable therapeutic options for rheumatologic patients. Phenotypes and endotypes are a promising approach to detect critically ill patients with hyper- or hypo-inflammation. Sepsis trials using biomarkers such as ferritin, lymphopenia, HLA-DR expression on monocytes and PD-L1 to guide immunotherapy have been already conducted or are currently ongoing. Immunotherapy in COVID-19 pneumonia, guided by C-reactive protein and soluble urokinase plasminogen activator receptor (suPAR) has improved patient outcomes globally. More research is needed into immunotherapy in other critical conditions.

EXPERT OPINION

Targeted immunotherapy has improved outcomes in oncology and rheumatology, paving the way for precision medicine in the critically ill. Transcriptomics will play a crucial role in detecting the most suitable candidates for immunomodulation.

Exploring the impact of clonal definition on B-cell diversity: implications for the analysis of immune repertoires

The adaptive immune system has the extraordinary ability to produce a broad range of immunoglobulins that can bind a wide variety of antigens. During adaptive immune responses, activated B cells duplicate and undergo somatic hypermutation in their B-cell receptor (BCR) genes, resulting in clonal families of diversified B cells that can be related back to a common ancestor. Advances in high-throughput sequencing technologies have enabled the high-throughput characterization of B-cell repertoires, however, the accurate identification of clonally related BCR sequences remains a major challenge. In this study, we compare three different clone identification methods on both simulated and experimental data, and investigate their impact on the characterization of B-cell diversity. We observe that different methods lead to different clonal definitions, which affects the quantification of clonal diversity in repertoire data. Our analyses show that direct comparisons between clonal clusterings and clonal diversity of different repertoires should be avoided if different clone identification methods were used to define the clones. Despite this variability, the diversity indices inferred from the repertoires' clonal characterization across samples show similar patterns of variation regardless of the clonal identification method used. We find the Shannon entropy to be the most robust in terms of the variability of diversity rank across samples. Our analysis also suggests that the traditional germline gene alignment-based method for clonal identification remains the most accurate when the complete information about the sequence is known, but that alignment-free methods may be preferred for shorter sequencing read lengths. We make our implementation freely available as a Python library cdiversity.

Understanding repertoire sequencing data through a multiscale computational model of the germinal center

Sequencing of B-cell and T-cell immune receptor repertoires helps us to understand the adaptive immune response, although it only provides information about the clonotypes (lineages) and their frequencies and not about, for example, their affinity or antigen (Ag) specificity. To further characterize the identified clones, usually with special attention to the particularly abundant ones (dominant), additional time-consuming or expensive experiments are generally required. Here, we present an extension of a multiscale model of the germinal center (GC) that we previously developed to gain more insight in B-cell repertoires. We compare the extent that these simulated repertoires deviate from experimental repertoires established from single GCs, blood, or tissue. Our simulations show that there is a limited correlation between clonal abundance and affinity and that there is large affinity variability among same-ancestor (same-clone) subclones. Our simulations suggest that low-abundance clones and subclones, might also be of interest since they may have high affinity for the Ag. We show that the fraction of plasma cells (PCs) with high B-cell receptor (BcR) mRNA content in the GC does not significantly affect the number of dominant clones derived from single GCs by sequencing BcR mRNAs. Results from these simulations guide data interpretation and the design of follow-up experiments.

Exploring the sheep (Ovis aries) immunoglobulin repertoire by next generation sequencing

Next-generation sequencing (NGS) has revolutionized the way we determine the antibody repertoires encoded by B cells in the blood or lymphoid organs and transformed our understanding of adaptive immune responses in many species. Sheep (Ovis aries) have been widely used as a host for therapeutic antibody production since the early 1980s, however, little is known about their immune repertoires or immunological processes affecting the antibody generation. The objective of this study was to employ NGS for a comprehensive analysis of immunoglobulin heavy and light chain repertoires in four healthy sheep. We obtained > 90 % complete antibody sequences and nearly 130,000, 48,000 and 218,000 unique CDR3 reads for the heavy chain (IGH), kappa chain (IGK), and lambda chain (IGL) loci, respectively. Consistent with other species, we observed biased usage of germline variable (V), diversity (D) and joining (J) genes in the heavy and kappa loci, but not in the lambda loci. Moreover, the enormous diversity of CDR3 sequences was observed through sequence clustering and convergent recombination. These data will build a foundation for future studies investigating immune repertoires in health and disease as well as contribute to further refinement of ovine-derived therapeutic antibody drugs.

Analyzing Antibody Repertoire Using Next-Generation Sequencing and Machine Learning

Advances in high-throughput sequencing technologies have enabled comprehensive sequencing of the immune repertoire. Since repertoire analysis can help to explain the relationship between the immune system and diseases, several methods have been developed for repertoire analysis. Here, using simulated and real-world datasets, we describe how to use DeepRC, a method that applies cutting-edge machine learning techniques.

A scalable model for simulating multi-round antibody evolution and benchmarking of clonal tree reconstruction methods

Affinity maturation (AM) of B cells through somatic hypermutations (SHMs) enables the immune system to evolve to recognize diverse pathogens. The accumulation of SHMs leads to the formation of clonal lineages of antibody-secreting b cells that have evolved from a common naïve B cell. Advances in high-throughput sequencing have enabled deep scans of B cell receptor repertoires, paving the way for reconstructing clonal trees. However, it is not clear if clonal trees, which capture microevolutionary time scales, can be reconstructed using traditional phylogenetic reconstruction methods with adequate accuracy. In fact, several clonal tree reconstruction methods have been developed to fix supposed shortcomings of phylogenetic methods. Nevertheless, no consensus has been reached regarding the relative accuracy of these methods, partially because evaluation is challenging. Benchmarking the performance of existing methods and developing better methods would both benefit from realistic models of clonal lineage evolution specifically designed for emulating B cell evolution. In this paper, we propose a model for modeling B cell clonal lineage evolution and use this model to benchmark several existing clonal tree reconstruction methods. Our model, designed to be extensible, has several features: by evolving the clonal tree and sequences simultaneously, it allows modeling selective pressure due to changes in affinity binding; it enables scalable simulations of large numbers of cells; it enables several rounds of infection by an evolving pathogen; and, it models building of memory. In addition, we also suggest a set of metrics for comparing clonal trees and measuring their properties. Our results show that while maximum likelihood phylogenetic reconstruction methods can fail to capture key features of clonal tree expansion if applied naively, a simple post-processing of their results, where short branches are contracted, leads to inferences that are better than alternative methods.

Association of IGHM polymorphisms with susceptibility to type 1 diabetes

Differentiation of B lymphocytes is accompanied by a regulated switch in the expression pattern and stability of surface and secretory immunoglobulins (Igs). Several lines of evidence show that autoimmune responses evolving in much autoimmune pathologies were associated with a high level of humoral Ig, but their pathogenic role remains elusive. The aim of this study was to test the hypothesis that variants at the immunoglobulin heavy-chain IGH locus are genetic determinants to T1D susceptibility. Here, we tested the genetic association of the variants of the immunoglobulin heavy-chain IGH locus as a genetic determinant to T1D susceptibility. A total of 255 subjects from 59 Tunisian families were genotyped for 15 SNPs mapping in 4 regions in IGH locus. We found that rs1950942, rs2180790, rs1808152, and rs1956596 of IGHM and rs2516751 variant located in the IGHA1/IGHG2 region were significantly associated with a risk for T1D p = 7E-3; p = 0.03; p = 0.02; p = 0.043; and p = 3.65E-5, respectively. The TATGG haplotype derived from LD across three SNPs from IGHM gene and two SNPs from IGHD gene was significantly over-transmitted from parents to affect offspring. Our results suggest that genetic variants at the IGH locus are associated with T1D susceptibility. These variations may predispose to IgG AutoAbs production against pancreatic antigens and AutoAbs multi-reactivity, leading to T1D development.

High-Throughput Sequencing of Complementarity Determining Region 3 in the Heavy Chain of B-Cell Receptor in Renal Transplant Recipients: A Preliminary Report

Background: Graft failure resulting from rejection or any other adverse event usually originates from an aberrant and/or exaggerated immune response and is often catastrophic in renal transplantation. So, it is essential to monitor patients’ immune status for detecting a rejection/graft failure early on. Methods: We monitored the sequence change of complementary determining region 3 (CDR3) in B-cell receptor (BCR) immunoglobulin heavy-chain (IGH) immune repertoire (iR) in 14 renal transplant patients using next-generation sequencing (NGS), correlating its diversity to various clinical events occurring after transplantation. BCR-IGH-CDR3 in peripheral blood mononuclear cells was sequenced along the post-transplantation course by NGS using the iRweb server. Results: Datasets covering VDJ regions of BCR-IGH-CDR3 indicated clonal diversity (D50) variations along the post-transplant course. Furthermore, principal component analysis showed the clustering of these sequence variations. A total of 544 shared sequences were identified before transplantation. D50 remained low in three patients receiving rituximab. Among them, one’s D50 resumed after 3 m, indicating graft tolerance. The D50 rapidly increased after grafting and decreased thereafter in four patients without rejection, decreased in two patients with T-cell-mediated rejection (TCMR) and exhibited a sharp down-sliding after 3 m in two patients receiving donations after cardiac death (DCD). In another two patients with TCMR, D50 was low just before individual episodes, but either became persistently low or returned to a plateau, depending on the failure or success of the immunosuppressive treatments. Shared CDR3 clonal expansions correlated to D50 changes. Agglomerative hierarchical clustering showed a commonly shared CDR3 sequence and at least two different clusters in five patients. Conclusions: Clonal diversity in BCR-IGH-CDR3 varied depending on clinical courses of 14 renal transplant patients, including B-cell suppression therapy, TCMR, DCD, and graft tolerance. Adverse events on renal graft failure might lead to different clustering of BCR iR. However, these preliminary data need further verification in further studies for the possible applications of iR changes as genetic expression biomarkers or laboratory parameters to detect renal graft failure/rejection earlier.

AbSE Workflow: Rapid Identification of the Coding Sequence and Linear Epitope of the Monoclonal Antibody at the Single-cell Level

Monoclonal antibody (mAb) has been widely used in immunity research and disease diagnosis and therapy. Antibody sequence and epitope are the prerequisites and basis of mAb applications, which determine the properties of antibodies and make the preparation of antibody-based molecules controllable and reliable. Here, we present the antibody sequence and epitope identification (AbSE) workflow, a time-saving and cost-effective route for rapid determination of antibody sequence and linear epitope of mAb even at the single-cell level. The feasibility and accuracy of the AbSE workflow were demonstrated through the identification and validation of the coding sequence and epitope of antihuman serum albumin (antiHSA) mAb. It can be inferred that the AbSE workflow is a powerful and universal approach for paired antibody-epitope sequence identification. It may characterize antibodies not only on a single hybridoma cell but also on any other antibody-secreting cells.

Mobilization of innate and adaptive antitumor immune responses by the RNP-targeting antibody ATRC-101

Immunotherapy approaches focusing on T cells have provided breakthroughs in treating solid tumors. However, there remains an opportunity to drive anticancer immune responses via other cell types, particularly myeloid cells. ATRC-101 was identified via a target-agnostic process evaluating antibodies produced by the plasmablast population of B cells in a patient with non-small cell lung cancer experiencing an antitumor immune response during treatment with checkpoint inhibitor therapy. Here, we describe the target, antitumor activity in preclinical models, and data supporting a mechanism of action of ATRC-101. Immunohistochemistry studies demonstrated tumor-selective binding of ATRC-101 to multiple nonautologous tumor tissues. In biochemical analyses, ATRC-101 appears to target an extracellular, tumor-specific ribonucleoprotein (RNP) complex. In syngeneic murine models, ATRC-101 demonstrated robust antitumor activity and evidence of immune memory following rechallenge of cured mice with fresh tumor cells. ATRC-101 increased the relative abundance of conventional dendritic cell (cDC) type 1 cells in the blood within 24 h of dosing, increased CD8+ T cells and natural killer cells in blood and tumor over time, decreased cDC type 2 cells in the blood, and decreased monocytic myeloid-derived suppressor cells in the tumor. Cellular stress, including that induced by chemotherapy, increased the amount of ATRC-101 target in tumor cells, and ATRC-101 combined with doxorubicin enhanced efficacy compared with either agent alone. Taken together, these data demonstrate that ATRC-101 drives tumor destruction in preclinical models by targeting a tumor-specific RNP complex leading to activation of innate and adaptive immune responses.

Moving beyond Titers

Vaccination to prevent and even eliminate disease is amongst the greatest achievements of modern medicine. Opportunities remain in vaccine development to improve protection across the whole population. A next step in vaccine development is the detailed molecular characterization of individual humoral immune responses against a pathogen, especially the rapidly evolving pathogens. New technologies such as sequencing the immune repertoire in response to disease, immunogenomics/vaccinomics, particularly the individual HLA variants, and high-throughput epitope characterization offer new insights into disease protection. Here, we highlight the emerging technologies that could be used to identify variation within the human population, facilitate vaccine discovery, improve vaccine safety and efficacy, and identify mechanisms of generating immunological memory. In today’s vaccine-hesitant climate, these techniques used individually or especially together have the potential to improve vaccine effectiveness and safety and thus vaccine uptake rates. We highlight the importance of using these techniques in combination to understand the humoral immune response as a whole after vaccination to move beyond neutralizing titers as the standard for immunogenicity and vaccine efficacy, especially in clinical trials.

Heterogeneous origin of IgE in atopic dermatitis and psoriasis revealed by B cell receptor repertoire analysis

BACKGROUND

Epicutaneous sensitization is an important route for the production of IgE, and skin inflammation-induced IgE has recently been reported having features of natural antibody. Atopic dermatitis (AD) and psoriasis have differentially increased level of serum IgE; however, the production mechanism of IgE in these inflammatory skin diseases remains unknown.

OBJECTIVE

To explore the origin of IgE in AD and psoriasis by analyzing the B cell receptor repertoire.

METHODS

mRNA was prepared from peripheral blood mononuclear cells of AD and psoriasis patients that had elevated serum levels of IgE, and immunoglobulin heavy chain (IGH) repertoires were sequenced after reverse transcription. Clonal lineages of B cells containing members expressing IgE were identified, and somatic hypermutations in IGH inherited from common ancestors within the clonal lineage were used to infer the relationships between B cells.

RESULTS

The proportions of IGHE from AD and psoriasis were higher than that of normal control, which were positively correlated with the levels of serum total IgE. The somatic hypermutation value of IGHE variable region was lower than that of IGHG and IGHA, but higher than IGHM and IGHD, indicating a mixed natural and adaptive origins of IgE; and psoriasis demonstrated lower level of hypermutation than AD. The Shannon indexes of CDR3 in IGHE of AD and psoriasis were higher than that of normal control, also supporting the natural origin. The VH usage of IgE was weakly biased in AD and psoriasis patients with high level of house dust mite-specific IgE. Comparison of the number of shared mutations in multi-isotype lineages containing IgE showed that isotype-switching from IgG-expressing B cells might be the major source of IgE in AD and psoriasis.

CONCLUSION

IgE has heterogeneous origin in AD and psoriasis, and skin inflammation may contribute to the increased production of natural IgE.

An Immunoproteomic Survey of the Antibody Landscape: Insights and Opportunities Revealed by Serological Repertoire Profiling

Immunoproteomics has emerged as a versatile tool for analyzing the antibody repertoire in various disease contexts. Until recently, characterization of antibody molecules in biological fluids was limited to bulk serology, which identifies clinically relevant features of polyclonal antibody responses. The past decade, however, has seen the rise of mass-spectrometry-enabled proteomics methods that have allowed profiling of the antibody response at the molecular level, with the disease-specific serological repertoire elucidated in unprecedented detail. In this review, we present an up-to-date survey of insights into the disease-specific immunological repertoire by examining how quantitative proteomics-based approaches have shed light on the humoral immune response to infection and vaccination in pathogenic illnesses, the molecular basis of autoimmune disease, and the tumor-specific repertoire in cancer. We address limitations of this technology with a focus on emerging potential solutions and discuss the promise of high-resolution immunoproteomics in therapeutic discovery and novel vaccine design.

Bringing precision oncology to cellular resolution with single-cell genomics

Single-cell sequencing technologies have undergone rapid development and adoption by the scientific community in the past 5 years, fueling discoveries about the etiology, pathogenesis, and treatment responsiveness of individual tumor cells within cancer ecosystems. Most of the advancements in our understanding of cancer with these new technologies have focused on basic tumor biology. However, the knowledge produced by these and other studies are beginning to provide biomarkers and drug targets for clinically-relevant subpopulations within a tumor, creating opportunities for the development of biologically-informed, clone-specific combination treatment strategies. Here we provide an overview of the development of the field of single-cell cancer sequencing and provide a roadmap for shepherding these technologies from research tools to diagnostic instruments that provide high-resolution, treatment-directing details of tumors to clinical oncologists.

AIRR Community Guide to Planning and Performing AIRR-Seq Experiments

The development of high-throughput sequencing of adaptive immune receptor repertoires (AIRR-seq of IG and TR rearrangements) has provided a new frontier for in-depth analysis of the immune system. The last decade has witnessed an explosion in protocols, experimental methodologies, and computational tools. In this chapter, we discuss the major considerations in planning a successful AIRR-seq experiment together with basic strategies for controlling and evaluating the outcome of the experiment. Members of the AIRR Community have authored several chapters in this edition, which cover step-by-step instructions to successfully conduct, analyze, and share an AIRR-seq project.

Dual UMIs and Dual Barcodes With Minimal PCR Amplification Removes Artifacts and Acquires Accurate Antibody Repertoire

Antibody repertoire sequencing (Rep-seq) has been widely used to reveal repertoire dynamics and to interrogate antibodies of interest at single nucleotide-level resolution. However, polymerase chain reaction (PCR) amplification introduces extensive artifacts including chimeras and nucleotide errors, leading to false discovery of antibodies and incorrect assessment of somatic hypermutations (SHMs) which subsequently mislead downstream investigations. Here, a novel approach named DUMPArts, which improves the accuracy of antibody repertoires by labeling each sample with dual barcodes and each molecule with dual unique molecular identifiers (UMIs) via minimal PCR amplification to remove artifacts, is developed. Tested by ultra-deep Rep-seq data, DUMPArts removed inter-sample chimeras, which cause artifactual shared clones and constitute approximately 15% of reads in the library, as well as intra-sample chimeras with erroneous SHMs and constituting approximately 20% of the reads, and corrected base errors and amplification biases by consensus building. The removal of these artifacts will provide an accurate assessment of antibody repertoires and benefit related studies, especially mAb discovery and antibody-guided vaccine design.

Immune cell and TCR/BCR repertoire profiling in systemic lupus erythematosus patients by single-cell sequencing

The immune cells and the repertoire of T cells and B cells play an important role in the pathogenesis of systemic lupus erythematosus (SLE). Exploring their expression and distribution in SLE can help us better understand this lethal autoimmune disease. In this study, we used a single-cell 5’ RNA sequence and single-cell T cell receptor (TCR)/B cell receptor (BCR) to study the immune cells and the repertoire from ten SLE patients and the paired normal controls (NC). The results showed that 9732 cells correspondence to 12 cluster immune cell types were identified in NC, whereas 11042 cells correspondence to 16 cluster immune cell types were identified in SLE. The results demonstrated that neutrophil, macrophage, and dendritic cells were accumulated in SLE by annotating the immune cell types. Besides, the bioinformatics analysis of differentially expressed genes (DEGs) in these cell types indicates their role in inflammation response. In addition, patients with SLE showed increased TCR and BCR clonotypes compared with the healthy controls. Furthermore, patients with SLE showed biased usage of TCR and BCR V(D)J genes. Taken together, we characterized the transcriptome and TCR/BCR immune repertoire profiles of SLE patients, which may provide a new avenue for the diagnosis and treatment of SLE.

Why current quantitative serology is not quantitative and how systems immunology could provide solutions

Determination of the presence of antibodies against infectious agents, self-antigens, allogeneic antigens and environmental antigens is the goal of medical serology. Along with the standardization of these tests the community also started to use the expression “quantitative serology,” referring to the fact that arbitrary units are used for the expression of results. In this review I will argue against the use of the term quantitative serology for current tests. Because each test and each antibody isotype determination uses its own references, the term semiquantitative better describes these methods. The introduction of really quantitative serology could both benefit from and drive forward systems immunological approach to immunity.

Progress and challenges in mass spectrometry-based analysis of antibody repertoires

Humoral immunity is divided into the cellular B cell and protein-level antibody responses. High-throughput sequencing has advanced our understanding of both these fundamental aspects of B cell immunology as well as aspects pertaining to vaccine and therapeutics biotechnology. Although the protein-level serum and mucosal antibody repertoire make major contributions to humoral protection, the sequence composition and dynamics of antibody repertoires remain underexplored. This limits insight into important immunological and biotechnological parameters such as the number of antigen-specific antibodies, which are for example, relevant for pathogen neutralization, microbiota regulation, severity of autoimmunity, and therapeutic efficacy. High-resolution mass spectrometry (MS) has allowed initial insights into the antibody repertoire. We outline current challenges in MS-based sequence analysis of antibody repertoires and propose strategies for their resolution.

RAPID: A Rep-Seq Dataset Analysis Platform With an Integrated Antibody Database

The antibody repertoire is a critical component of the adaptive immune system and is believed to reflect an individual’s immune history and current immune status. Delineating the antibody repertoire has advanced our understanding of humoral immunity, facilitated antibody discovery, and showed great potential for improving the diagnosis and treatment of disease. However, no tool to date has effectively integrated big Rep-seq data and prior knowledge of functional antibodies to elucidate the remarkably diverse antibody repertoire. We developed a Rep-seq dataset Analysis Platform with an Integrated antibody Database (RAPID; https://rapid.zzhlab.org/), a free and web-based tool that allows researchers to process and analyse Rep-seq datasets. RAPID consolidates 521 WHO-recognized therapeutic antibodies, 88,059 antigen- or disease-specific antibodies, and 306 million clones extracted from 2,449 human IGH Rep-seq datasets generated from individuals with 29 different health conditions. RAPID also integrates a standardized Rep-seq dataset analysis pipeline to enable users to upload and analyse their datasets. In the process, users can also select set of existing repertoires for comparison. RAPID automatically annotates clones based on integrated therapeutic and known antibodies, and users can easily query antibodies or repertoires based on sequence or optional keywords. With its powerful analysis functions and rich set of antibody and antibody repertoire information, RAPID will benefit researchers in adaptive immune studies.

The methods and advances of adaptive immune receptors repertoire sequencing

The adaptive immune response is a powerful tool, capable of recognizing, binding to, and neutralizing a vast number of internal and external threats via T or B lymphatic receptors with widespread sets of antigen specificities. The emergence of high-throughput sequencing technology and bioinformatics provides opportunities for research in the fields of life sciences and medicine. The analysis and annotation for immune repertoire data can reveal biologically meaningful information, including immune prediction, target antigens, and effective evaluation. Continuous improvements of the immunological repertoire sequencing methods and analysis tools will help to minimize the experimental and calculation errors and realize the immunological information to meet the clinical requirements. That said, the clinical application of adaptive immune repertoire sequencing requires appropriate experimental methods and standard analytical tools. At the population cell level, we can acquire the overview of cell groups, but the information about a single cell is not obtained accurately. The information that is ignored may be crucial for understanding the heterogeneity of each cell, gene expression and drug response. The combination of high-throughput sequencing and single-cell technology allows us to obtain single-cell information with low-cost and high-throughput. In this review, we summarized the current methods and progress in this area.

Lower Somatic Mutation Levels in the λ Light-Chain Repertoires with Chronic HBV Infection

To investigate the characteristics of the immunoglobulin light-chain repertoires with chronic HBV infection, the high-throughput sequencing and IMGT/HighV-QUEST were adapted to analyze the κ (IgK) and λ (IgL) light-chain repertoires from the inactive HBV carriers (IHB) and the healthy adults (HH). The comparative analysis revealed high similarity between the κ light-chain repertoires of the HBV carriers and the healthy adults. Nevertheless, the proportion of IGLV genes with ≥90% identity as the germline genes was higher in the IgL light-chain repertoire of the IHB library compared with that of HH library (74.6% vs. 69.1%). Besides, the frequency of amino acid mutations in the CDR1 regions was significantly lower in the IgL light-chain repertoire of the IHB library than that of the HH library (65.52% vs. 56.0%). These results suggested the lower somatic mutation level in the IgL repertoire of IHB library, which might indicate the biased selection of IGLV genes in the IgL repertoire with chronic HBV infection. These findings might lead to a better understanding of the characteristics of the light-chain repertoires of HBV chronically infected individuals.

Mass Spectrometry-Based De Novo Sequencing of Monoclonal Antibodies Using Multiple Proteases and a Dual Fragmentation Scheme

Antibody sequence information is crucial to understanding the structural basis for antigen binding and enables the use of antibodies as therapeutics and research tools. Here, we demonstrate a method for direct de novo sequencing of monoclonal IgG from the purified antibody products. The method uses a panel of multiple complementary proteases to generate suitable peptides for de novo sequencing by liquid chromatography-tandem mass spectrometry (LC-MS/MS) in a bottom-up fashion. Furthermore, we apply a dual fragmentation scheme, using both stepped high-energy collision dissociation (stepped HCD) and electron-transfer high-energy collision dissociation (EThcD), on all peptide precursors. The method achieves full sequence coverage of the monoclonal antibody herceptin, with an accuracy of 99% in the variable regions. We applied the method to sequence the widely used anti-FLAG-M2 mouse monoclonal antibody, which we successfully validated by remodeling a high-resolution crystal structure of the Fab and demonstrating binding to a FLAG-tagged target protein in Western blot analysis. The method thus offers robust and reliable sequences of monoclonal antibodies.

Prospective Artificial Intelligence to Dissect the Dengue Immune Response and Discover Therapeutics

Dengue virus (DENV) poses a serious threat to global health as the causative agent of dengue fever. The virus is endemic in more than 128 countries resulting in approximately 390 million infection cases each year. Currently, there is no approved therapeutic for treatment nor a fully efficacious vaccine. The development of therapeutics is confounded and hampered by the complexity of the immune response to DENV, in particular to sequential infection with different DENV serotypes (DENV1-5). Researchers have shown that the DENV envelope (E) antigen is primarily responsible for the interaction and subsequent invasion of host cells for all serotypes and can elicit neutralizing antibodies in humans. The advent of high-throughput sequencing and the rapid advancements in computational analysis of complex data, has provided tools for the deconvolution of the DENV immune response. Several types of complex statistical analyses, machine learning models and complex visualizations can be applied to begin answering questions about the B- and T-cell immune responses to multiple infections, antibody-dependent enhancement, identification of novel therapeutics and advance vaccine research.

Biological controls for standardization and interpretation of adaptive immune receptor repertoire profiling

Use of adaptive immune receptor repertoire sequencing (AIRR-seq) has become widespread, providing new insights into the immune system with potential broad clinical and diagnostic applications. However, like many high-throughput technologies, it comes with several problems, and the AIRR Community was established to understand and help solve them. We, the AIRR Community’s Biological Resources Working Group, have surveyed scientists about the need for standards and controls in generating and annotating AIRR-seq data. Here, we review the current status of AIRR-seq, provide the results of our survey, and based on them, offer recommendations for developing AIRR-seq standards and controls, including future work.

The Future of Blood Testing Is the Immunome

It is increasingly clear that an extraordinarily diverse range of clinically important conditions—including infections, vaccinations, autoimmune diseases, transplants, transfusion reactions, aging, and cancers—leave telltale signatures in the millions of V(D)J-rearranged antibody and T cell receptor [TR per the Human Genome Organization (HUGO) nomenclature but more commonly known as TCR] genes collectively expressed by a person’s B cells (antibodies) and T cells. We refer to these as the immunome. Because of its diversity and complexity, the immunome provides singular opportunities for advancing personalized medicine by serving as the substrate for a highly multiplexed, near-universal blood test. Here we discuss some of these opportunities, the current state of immunome-based diagnostics, and highlight some of the challenges involved. We conclude with a call to clinicians, researchers, and others to join efforts with the Adaptive Immune Receptor Repertoire Community (AIRR-C) to realize the diagnostic potential of the immunome.

Alignment free identification of clones in B cell receptor repertoires

Following antigenic challenge, activated B cells rapidly expand and undergo somatic hypermutation, yielding groups of clonally related B cells with diversified immunoglobulin receptors. Inference of clonal relationships based on the receptor sequence is an essential step in many adaptive immune receptor repertoire sequencing studies. These relationships are typically identified by a multi-step process that involves: (i) grouping sequences based on shared V and J gene assignments, and junction lengths and (ii) clustering these sequences using a junction-based distance. However, this approach is sensitive to the initial gene assignments, which are error-prone, and fails to identify clonal relatives whose junction length has changed through accumulation of indels. Through defining a translation-invariant feature space in which we cluster the sequences, we develop an alignment free clonal identification method that does not require gene assignments and is not restricted to a fixed junction length. This alignment free approach has higher sensitivity compared to a typical junction-based distance method without loss of specificity and PPV. While the alignment free procedure identifies clones that are broadly consistent with the junction-based distance method, it also identifies clones with characteristics (multiple V or J gene assignments or junction lengths) that are not detectable with the junction-based distance method.

An Evolutionary Arms Race Between Burkholderia pseudomallei and Host Immune System: What Do We Know?

A better understanding of co-evolution between pathogens and hosts holds promise for better prevention and control strategies. This review will explore the interactions between Burkholderia pseudomallei, an environmental and opportunistic pathogen, and the human host immune system. B. pseudomallei causes "Melioidosis," a rapidly fatal tropical infectious disease predicted to affect 165,000 cases annually worldwide, of which 89,000 are fatal. Genetic heterogeneities were reported in both B. pseudomallei and human host population, some of which may, at least in part, contribute to inter-individual differences in disease susceptibility. Here, we review (i) a multi-host-pathogen characteristic of the interaction; (ii) selection pressures acting on B. pseudomallei and human genomes with the former being driven by bacterial adaptation across ranges of ecological niches while the latter are driven by human encounter of broad ranges of pathogens; (iii) the mechanisms that generate genetic diversity in bacterial and host population particularly in sequences encoding proteins functioning in host-pathogen interaction; (iv) reported genetic and structural variations of proteins or molecules observed in B. pseudomallei-human host interactions and their implications in infection outcomes. Together, these predict bacterial and host evolutionary trajectory which continues to generate genetic diversity in bacterium and operates host immune selection at the molecular level.

A computational method for immune repertoire mining that identifies novel binders from different clonotypes, demonstrated by identifying anti-pertussis toxoid antibodies

Due to their shared genetic history, antibodies from the same clonotype often bind to the same epitope. This knowledge is used in immune repertoire mining, where known binders are used to search bulk sequencing repertoires to identify new binders. However, current computational methods cannot identify epitope convergence between antibodies from different clonotypes, limiting the sequence diversity of antigen-specific antibodies that can be identified. We describe how the antibody binding site, the paratope, can be used to cluster antibodies with common antigen reactivity from different clonotypes. Our method, paratyping, uses the predicted paratope to identify these novel cross clonotype matches. We experimentally validated our predictions on a pertussis toxoid dataset. Our results show that even the simplest abstraction of the antibody binding site, using only the length of the loops involved and predicted binding residues, is sufficient to group antigen-specific antibodies and provide additional information to conventional clonotype analysis.

Abbreviations: BCR: B-cell receptor; CDR: complementarity-determining region; PTx: pertussis toxoid

Beyond bulk single-chain sequencing: Getting at the whole receptor

Recent advancements in paired B-cell receptor sequencing technologies have accelerated the development of simpler, high-throughput pipelines for generating native antibody heavy and light chain pairs used to elucidate novel antibodies and provide insights into antibody response against pathogenic targets. These technologies involve single-cell isolation, using either single wells or emulsified droplets to maintain physical separation of individual cells, followed by sequencing. The development of novel single wells and emulsion-based workflows addresses key challenges by improving throughput of single-cell analyses, reducing method complexity, and integrating functional assays into existing workflows. Enabled by paired B-cell receptor sequencing, functional characterization of pathogen-specific antibodies reveals immunological insights beyond bulk sequencing.

Characterization of Variable Region Genes and Discovery of Key Recognition Sites in the Complementarity Determining Regions of the Anti-Thiacloprid Monoclonal Antibody

Sequence-defined recombinant antibodies (rAbs) have emerged as alternatives to hybridoma-secreted monoclonal antibodies (mAbs) for performing immunoassays. However, the polyploidy nature of hybridomas often leads to the coexistence of aberrant or non-specific functional variable region (VR) gene transcripts, which complicates the identification of correct VR sequences. Herein, we introduced the use of LC-MS/MS combined with next-generation sequencing to characterize VR sequences in an anti-thiacloprid mAb, which was produced by a hybridoma with genetic antibody diversity. The certainty of VR sequences was verified by the functional analysis based on the recombinant antibody (rAb) expressed by HEK293 mammalian cells. The performance of the rAb was similar to that of the parental mAb, with IC50 values of 0.73 and 0.46 μg/L as measured by ELISAs. Moreover, molecular docking analysis revealed that Ser52 (H-CDR2), Trp98, and Trp93 (L-CDR3) residues in the complementarity determining regions (CDRs) of the identified VR sequences predominantly contributed to thiacloprid-specific recognition through hydrogen bonds and the CH-π interaction. Through single-site-directed alanine mutagenesis, we found that Trp98 and Trp93 (L-CDR3) showed high affinity to thiacloprid, while Ser52 (H-CDR2) had an auxiliary effect on the specific binding. This study presents an efficient and reliable way to determine the key recognition sites of hapten-specific mAbs, facilitating the improvement of antibody properties.

Benchmarking immunoinformatic tools for the analysis of antibody repertoire sequences

Summary

Antibody repertoires reveal insights into the biology of the adaptive immune system and empower diagnostics and therapeutics. There are currently multiple tools available for the annotation of antibody sequences. All downstream analyses such as choosing lead drug candidates depend on the correct annotation of these sequences; however, a thorough comparison of the performance of these tools has not been investigated. Here, we benchmark the performance of commonly used immunoinformatic tools, i.e. IMGT/HighV-QUEST, IgBLAST and MiXCR, in terms of reproducibility of annotation output, accuracy and speed using simulated and experimental high-throughput sequencing datasets.

We analyzed changes in IMGT reference germline database in the last 10 years in order to assess the reproducibility of the annotation output. We found that only 73/183 (40%) V, D and J human genes were shared between the reference germline sets used by the tools. We found that the annotation results differed between tools. In terms of alignment accuracy, MiXCR had the highest average frequency of gene mishits, 0.02 mishit frequency and IgBLAST the lowest, 0.004 mishit frequency. Reproducibility in the output of complementarity determining three regions (CDR3 amino acids) ranged from 4.3% to 77.6% with preprocessed data. In addition, run time of the tools was assessed: MiXCR was the fastest tool for number of sequences processed per unit of time. These results indicate that immunoinformatic analyses greatly depend on the choice of bioinformatics tool. Our results support informed decision-making to immunoinformaticians based on repertoire composition and sequencing platforms.

Availability and implementation

All tools utilized in the paper are free for academic use.

Supplementary information

Supplementary data are available at Bioinformatics online.

Beyond Allotypes: The Influence of Allelic Diversity in Antibody Constant Domains

Polymorphic diversity in antibody constant domains has long been defined by allotypic motifs that cross react with the sera of other individuals. Improvements in sequencing technologies have led to the discovery of a large number of new allelic sequences that underlie this diversity. Many of the point mutations lie outside traditional allotypic motifs suggesting they do not elicit immunogenic responses. As antibodies play an important role in immune defense and biotechnology, understanding how this newly resolved diversity influences the function of antibodies is important. This review investigates the current known diversity of antibody alleles at a protein level for each antibody isotype as well as the kappa and lambda light chains. We focus on evidence emerging for how these mutations perturb antibody interactions with antigens and Fc receptors that are critical for function, as well as the influence this might have on the use of antibodies as therapeutics and reagents.

IgM Antibody Repertoire Fingerprints in Mice Are Personalized but Robust to Viral Infection Status

Antibody repertoire sequencing provides a molecular fingerprint of current and past pathogens encountered by the immune system. Most repertoire studies in humans require measuring the B cell response in the blood, resulting in a large bias to the IgM isotype. The extent to which the circulating IgM antibody repertoire correlates to lymphoid tissue-resident B cells in the setting of viral infection remains largely uncharacterized. Therefore, we compared the IgM repertoires from both blood and bone marrow (BM) plasma cells (PCs) following acute or chronic lymphocytic choriomeningitis virus (LCMV) infection in mice. Despite previously reported serum alterations between acute and chronic infection, IgM repertoire signatures based on clonal diversity metrics, public clones, network, and phylogenetic analysis were largely unable to distinguish infection cohorts. Our findings, however, revealed mouse-specific repertoire fingerprints between the blood and PC repertoires irrespective of infection status.

High-throughput single-cell activity-based screening and sequencing of antibodies using droplet microfluidics

Mining the antibody repertoire of plasma cells and plasmablasts could enable the discovery of useful antibodies for therapeutic or research purposes¹. We present a method for high-throughput, single-cell screening of IgG-secreting primary cells to characterize antibody binding to soluble and membrane-bound antigens. CelliGO is a droplet microfluidics system that combines high-throughput screening for IgG activity, using fluorescence-based in-droplet single-cell bioassays², with sequencing of paired antibody V genes, using in-droplet single-cell barcoded reverse transcription. We analyzed IgG repertoire diversity, clonal expansion and somatic hypermutation in cells from mice immunized with a vaccine target, a multifunctional enzyme or a membrane-bound cancer target. Immunization with these antigens yielded 100-1,000 IgG sequences per mouse. We generated 77 recombinant antibodies from the identified sequences and found that 93% recognized the soluble antigen and 14% the membrane antigen. The platform also allowed recovery of ~450-900 IgG sequences from ~2,200 IgG-secreting activated human memory B cells, activated ex vivo, demonstrating its versatility.

Adaptive immune receptor repertoires, an overview of this exciting field

The adaptive immune response in jawed vertebrates relies on the huge diversity and specificity of the B cell and T cell antigen receptors, the immunoglobulins (IG) or antibodies and the T cell receptors (TR), respectively. The high level of diversity has represented a barrier to a comprehensive analysis of the adaptive immune response before the emergence of high-throughput sequencing (HTS) technologies. The size and complexity of HTS data requires the generation of novel computational and analytical approaches, which are transforming how the adaptive immune responses are deciphered to understand the clonal dynamics and properties of antigen-specific B and T cells in response to different kind of antigens. This exciting and rapidly evolving field is not only impacting human and clinical immunology but also comparative immunology. We are now closer to understanding the evolution of adaptive immune response in jawed vertebrates. This review provides an overview about classical and current strategies developed to assess the IG/TR diversity and their applications in basic and clinical immunology.

VDJbase: an adaptive immune receptor genotype and haplotype database

VDJbase is a publicly available database that offers easy searching of data describing the complete sets of gene sequences (genotypes and haplotypes) inferred from adaptive immune receptor repertoire sequencing datasets. VDJbase is designed to act as a resource that will allow the scientific community to explore the genetic variability of the immunoglobulin (Ig) and T cell receptor (TR) gene loci. It can also assist in the investigation of Ig- and TR-related genetic predispositions to diseases. Our database includes web-based query and online tools to assist in visualization and analysis of the genotype and haplotype data. It enables users to detect those alleles and genes that are significantly over-represented in a particular population, in terms of genotype, haplotype and gene expression. The database website can be freely accessed at https://www.vdjbase.org/, and no login is required. The data and code use creative common licenses and are freely downloadable from https://bitbucket.org/account/user/yaarilab/projects/GPHP.

Rheumatoid arthritis patients display B-cell dysregulation already in the naïve repertoire consistent with defects in B-cell tolerance

B cells are postulated to be central in seropositive rheumatoid arthritis (RA). Here, we use exploratory mass cytometry (n = 23) and next-generation sequencing (n = 19) to study B-cell repertoire shifts in RA patients. Expression of several B-cell markers were significantly different in ACPA⁺ RA compared to healthy controls, including an increase in HLA-DR across subsets, CD22 in clusters of IgM⁺ B cells and CD11c in IgA⁺ memory. Moreover, both IgA⁺ and IgG⁺ double negative (IgD⁻ CD27⁻) CD11c⁺ B cells were increased in ACPA⁺ RA, and there was a trend for elevation in a CXCR5/CCR6^high transitional B-cell cluster. In the RA BCR repertoire, there were significant differences in subclass distribution and, notably, the frequency of VH with low somatic hypermutation (SHM) was strikingly higher, especially in IgG1 (p < 0.0001). Furthermore, both ACPA⁺ and ACPA⁻ RA patients had significantly higher total serum IgA and IgM compared to controls, based on serology of larger cohorts (n = 3494 IgA; n = 397 IgM). The observed elevated Ig-levels, distortion in IgM⁺ B cells, increase in double negative B cells, change in B-cell markers, and elevation of unmutated IgG⁺ B cells suggests defects in B-cell tolerance in RA. This may represent an underlying cause of increased polyreactivity and autoimmunity in RA.

Immunoglobulin profiling identifies unique signatures in patients with Kawasaki disease during intravenous immunoglobulin treatment

Identifying the causes of high fever syndromes such as Kawasaki disease (KD) remains challenging. To investigate pathogen exposure signatures in suspected pathogen-mediated diseases such as KD, we performed immunoglobulin (Ig) profiling using a next-generation sequencing method. After intravenous Ig (IVIG) treatment, we observed disappearance of clonally expanded IgM clonotypes, which were dominantly observed in acute-phase patients. The complementary-determining region 3 (CDR3) sequences of dominant IgM clonotypes in acute-phase patients were commonly observed in other Ig isotypes. In acute-phase KD patients, we identified 32 unique IgM CDR3 clonotypes shared in three or more cases. Furthermore, before the IVIG treatment, the sums of dominant IgM clonotypes in IVIG-resistant KD patients were significantly higher than those of IVIG-sensitive KD patients. Collectively, we demonstrate a novel approach for identifying certain Ig clonotypes for potentially interacting with pathogens involved in KD; this approach could be applied for a wide variety of fever-causing diseases of unknown origin.

Next-generation sequencing-guided identification and reconstruction of antibody CDR combinations from phage selection outputs

Next-generation sequencing (NGS) technologies have been employed in several phage display platforms for analyzing natural and synthetic antibody sequences and for identifying and reconstructing single-chain variable fragments (scFv) and antigen-binding fragments (Fab) not found by conventional ELISA screens. In this work, we developed an NGS-assisted antibody discovery platform by integrating phage-displayed, single-framework, synthetic Fab libraries. Due to limitations in attainable read and amplicon lengths, NGS analysis of Fab libraries and selection outputs is usually restricted to either V_H or V_L. Since this information alone is not sufficient for high-throughput reconstruction of Fabs, we developed a rapid and simple method for linking and sequencing all diversified CDRs in phage Fab pools. Our method resulted in a reliable and straightforward platform for converting NGS information into Fab clones. We used our NGS-assisted Fab reconstruction method to recover low-frequency rare clones from phage selection outputs. While previous studies chose rare clones for rescue based on their relative frequencies in sequencing outputs, we chose rare clones for reconstruction from less-frequent CDRH3 lengths. In some cases, reconstructed rare clones (frequency ∼0.1%) showed higher affinity and better specificity than high-frequency top clones identified by Sanger sequencing, highlighting the significance of NGS-based approaches in synthetic antibody discovery.

Cutting Edge: Ig H Chains Are Sufficient to Determine Most B Cell Clonal Relationships

B cell clonal expansion is vital for adaptive immunity. High-throughput BCR sequencing enables investigating this process but requires computational inference to identify clonal relationships. This inference usually relies on only the BCR H chain, as most current protocols do not preserve H:L chain pairing. The extent to which paired L chains aids inference is unknown. Using human single-cell paired BCR datasets, we assessed the ability of H chain-based clonal clustering to identify clones. Of the expanded clones identified, <20% grouped cells expressing inconsistent L chains. H chains from these misclustered clones contained more distant junction sequences and shared fewer V segment mutations than the accurate clones. This suggests that additional H chain information could be leveraged to refine clonal relationships. Conversely, L chains were insufficient to refine H chain-based clonal clusters. Overall, the BCR H chain alone is sufficient to identify clonal relationships with confidence.